Meat quality inspection system

Abstract

This report details the development and design of the Meat Quality Inspection System (MQIS), an innovative solution aimed at enhancing the meat quality assessment process through advanced technological integration. The MQIS leverages Artificial Intelligence and machine learning to provide accurate, efficient, and objective evaluations of meat quality, addressing critical industry challenges such as ensuring consistent product quality, complying with safety standards, and meeting consumer demand for high-quality meat products. The system architecture is modular, comprising several subsystems including User Interface, Image Processing, Analysis, and Database Management. Each subsystem collaborates to deliver comprehensive functionalities, from capturing and processing meat sample images to analyzing quality indicators and managing historical data. The user interface facilitates seamless interactions, enabling users to upload images, receive feedback. The report provides a thorough overview of the system's architectural design, data handling, and user interface design, highlighting the integration of image recognition and machine learning algorithms to ensure precise and reliable meat quality assessments. Project link http://github.com/Nesterk5/BSE24-16-final_year_project